This proposal seeks to address the problem of drug resistance to nonnucleoside inhibitors of HIV-1 reverse transcriptase (NNRTIs) through the refinement and extension of our computational methodology for predicting drug activity prior to synthesis and clinical testing. The goal is to build upon our past accomplishments in the use of Monte Carlo (MC) simulations coupled with a linear response (LR) method to predict activity against variant forms of RT (Y181C, Y188C, L1001, V106A, K101 E, K103N, and possible double mutants) that are resistant to all current anti-AIDS drugs. Hybrid quantum mechanics/molecular mechanics (QM/MM) refinements to the MC methodology and routines for protein backbone approximation will be incorporated to improve the accuracy of predictions. A new, rapid preliminary screening technique employing a combinatorial computational approach will be used to evaluate candidate structures prior to full computational evaluation. The proposed changes in methodology are anticipated to significantly improve the treatment of both the inhibitor and the protein backbone, problems of paramount importance if computational methods are to succeed in accurately predicting host-guest interactions in novel systems. The overall goal is to enhance the speed and accuracy of designing effective inhibitors of resistant forms of RT. The new methodology will be employed in the design of new members of a novel class of NNRTI's, BPBrs, developed in conjunction with collaborators at NCI-Frederick. Newly proposed BPBI analogs showing good predicted activity against variant forms of RT will be synthesized and tested for broad spectrum activity. While a specific and extremely important objective of the proposal is to discover new inhibitors targeted toward NNIRT resistant viruses found in AIDS patients, the general computational methodology developed herein has broad applications to the accurate description of binding in all host-guest interactions that involve proteins and organic molecules.